Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/02—Services making use of location information
  • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
  • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
  • G06F21/55—Detecting local intrusion or implementing counter-measures
  • G06F21/554—Detecting local intrusion or implementing counter-measures involving event detection and direct action
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
  • G06F21/70—Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer
  • G06F21/88—Detecting or preventing theft or loss
• • G—PHYSICS
  • G08—SIGNALLING
  • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
  • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
  • G08B21/18—Status alarms
  • G08B21/24—Reminder alarms, e.g. anti-loss alarms
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04M—TELEPHONIC COMMUNICATION
  • H04M1/00—Substation equipment, e.g. for use by subscribers
  • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
  • H04M1/724—User interfaces specially adapted for cordless or mobile telephones
  • H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
  • H04M1/72454—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to context-related or environment-related conditions
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
  • H04W12/12—Detection or prevention of fraud
  • H04W12/126—Anti-theft arrangements, e.g. protection against subscriber identity module [SIM] cloning
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/02—Services making use of location information
  • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/02—Services making use of location information
  • H04W4/029—Location-based management or tracking services
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W8/00—Network data management
  • H04W8/005—Discovery of network devices, e.g. terminals
• • G—PHYSICS
  • G08—SIGNALLING
  • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
  • G08B13/00—Burglar, theft or intruder alarms
  • G08B13/02—Mechanical actuation
  • G08B13/14—Mechanical actuation by lifting or attempted removal of hand-portable articles
  • G08B13/1427—Mechanical actuation by lifting or attempted removal of hand-portable articles with transmitter-receiver for distance detection
• • G—PHYSICS
  • G08—SIGNALLING
  • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
  • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
  • G08B21/02—Alarms for ensuring the safety of persons
  • G08B21/0202—Child monitoring systems using a transmitter-receiver system carried by the parent and the child
  • G08B21/0227—System arrangements with a plurality of child units
• • G—PHYSICS
  • G08—SIGNALLING
  • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
  • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
  • G08B21/02—Alarms for ensuring the safety of persons
  • G08B21/0202—Child monitoring systems using a transmitter-receiver system carried by the parent and the child
  • G08B21/0277—Communication between units on a local network, e.g. Bluetooth, piconet, zigbee, Wireless Personal Area Networks [WPAN]
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L67/00—Network arrangements or protocols for supporting network services or applications
  • H04L67/50—Network services
  • H04L67/535—Tracking the activity of the user
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
  • H04W12/60—Context-dependent security
  • H04W12/63—Location-dependent; Proximity-dependent
  • H04W12/64—Location-dependent; Proximity-dependent using geofenced areas
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Definitions

• the invention relates to a method of monitoring objects capable of wireless communications, a device for monitoring objects capable of wireless
• NFC Near-Field Communication
• RFID RFID
• the user has to configure a tracker application/device and the device(s) to be tracked, after which the tracker issues alarms if the tracked device(s) is/are not in proximity of the tracker, i.e., is/are outside a predetermined range from the tracker.
• a tracker application/device and the device(s) to be tracked, after which the tracker issues alarms if the tracked device(s) is/are not in proximity of the tracker, i.e., is/are outside a predetermined range from the tracker.
• a child may be provided with a tracked device in the form of a small radio transmitter, and the tracker device will sound an alarm if the child moves outside of a pre-defined area.
• An object of the present invention is to solve, or at least mitigate, this problem in the art and to provide an improved method of monitoring objects capable of wireless communications .
• This object is attained in a first aspect of the invention by a method of monitoring objects capable of wireless communications.
• the method comprises detecting an activity performed by a user of a wireless communications device, acquiring information identifying an expected set of objects which are associated with the detected activity, determining whether at least one of the objects in the expected set is not in proximity of the wireless communications device, and if so notifying the user that at least one of the objects in the expected set is not in proximity of the wireless communications device.
• a device for monitoring objects capable of wireless communications
• the device comprising a processing unit and a memory.
• the memory contains instructions executable by the processing unit, whereby the device is operative to detect an activity performed by a user of a wireless communications device, acquire information identifying an expected set of objects which are associated with the detected activity, determine whether at least one of the objects in the expected set is not in proximity of the wireless
• a device referred to as a tracker device being for instance a mobile phone, a mobile terminal, a User Equipment (UE), or a smartphone of a user, detects that a certain activity is performed by the user. For instance, it may be detected that the user performs an activity such as "Go To Work” upon leaving her home premises during a time window specified for the activity ("Any Weekday, 07:00-08:00").
• an activity such as "Go To Work” upon leaving her home premises during a time window specified for the activity ("Any Weekday, 07:00-08:00").
• a change in location of the user may, e.g., be detected using a Global Positioning System (GPS) of the tracker device (from a first location "on home premises” to a second location “off home premises", or “leaving home premises”).
• GPS Global Positioning System
• NFC Near Field Communication
• RFID Radio-Frequency Identification
• Bluetooth transmitter any other short-range radio transmitter
• the user is notified accordingly.
• the user is advantageously notified accordingly.
• the user is thus made aware that she forgot one or more of the objects of the expected set associated with this particular activity and can go back into her house to pick up any forgotten object of the expected set before leaving for work.
• the user is notified by the tracker device emitting an audible sound, displaying a message, generating a haptic notification such as a vibration, etc.
• the tracker device may signal another wireless communications device that the user should be notified, for instance by requesting the user's smartwatch to vibrate, or requesting the user's car to not start the engine and/or display a message on the dashboard.
• the method of monitoring the objects may be performed by the tracker device, a node of a communications network which is accessible by the wireless
• the communications device e.g., an application server, or one or more nodes of a cloud environment which is accessible by the wireless communications device. It is envisaged that a distributed solution may be provided, wherein the tracker device performs one or more steps of the method, while one or more cloud devices performs any further steps.
• an actual set of objects which are in proximity of the wireless communications device is determined, and it is further determined whether at least one of the objects in the expected set is not in the actual set. If so, the user is notified accordingly.
• an updated expected set may be stored in a database comprising activities and corresponding expected sets of objects.
• an updated expected set may be stored in a database comprising activities and corresponding expected sets of objects.
• the activity which is performed by the user of the wireless communications device is detected based on at least one of, a combination, or a pattern, of: a location of the wireless communications device or a change thereof, a motion pattern of the wireless communications device or a change thereof, a date, a time of day, a calendar event, a communication event, sensor readings, and current weather conditions.
• a behaviour of the user is registered, and if it is concluded that the registered behaviour is a frequently occurring behaviour of the user, the registered behaviour is specified as an activity.
• a group of objects are registered as being carried by the user when the frequently occurring behaviour of the user is registered, the group of objects being specified as the expected set of objects associated with the specified activity.
• a computer program comprising computer-executable instructions for causing the device to perform steps according to an embodiment of the first aspect of the invention, when the computer-executable instructions are executed on a processing unit included in the device.
• a computer program product comprising a computer readable medium, the computer readable medium having an embodiment of the computer program embodied thereon.
• Figure 1 illustrates a scenario where a user of a wireless communications device is monitored leaving the home premises for work, in accordance with embodiments of the invention.
• Figure 2 shows a flowchart illustrating an embodiment of a method of monitoring objects capable of wireless communications.
• Figure 3 shows a sequence diagram illustrating the embodiment of the method of monitoring objects capable of wireless communications according to Figure 2, performed by the wireless communications device of the user.
• Figure 4 shows a sequence diagram illustrating an embodiment of the method of monitoring objects capable of wireless communications, performed by a remotely located network node.
• Figure 5 shows a sequence diagram illustrating another embodiment of the method of monitoring objects capable of wireless communications.
• Figure 6 shows a sequence diagram illustrating yet another embodiment of the method of monitoring objects capable of wireless communications.
• Figure 7 shows a sequence diagram illustrating still another embodiment of the method of monitoring objects capable of wireless communications.
• Figure 8 shows a sequence diagram illustrating still a further embodiment of the method of monitoring objects capable of wireless communications.
• Figure 9 shows a sequence diagram illustrating yet a further embodiment of the method of monitoring objects capable of wireless communications.
• Figure 10 shows a device for monitoring objects capable of wireless
• Figure 11 shows a device configured to monitor objects capable of wireless communications, in accordance with another embodiment of the invention.
• Figure 1 illustrates an exemplifying embodiment of the invention.
• an individual or user 10 leaves home 11 for work every morning, she will want to bring with her a set of objects that she will need during her work day, which set in this particular example is exemplified as comprising her wallet 12, home key 13, and work pass 14 to be used for entering work premises.
• This set 15 of objects is referred to as the expected set of objects. That is, when the individual 10 with which the objects 12, 13, 14 are associated leaves home for work, she 10 is expected to carry the objects in the expected set 15 with her.
• Individual 10 further carries a wireless communications device 16, in Figure 1 exemplified as a smartphone 16.
• This wireless communications device 16 is referred to as a tracker device.
• NFC Near Field Communication
• RFID Radio-Frequency Identification
• wireless communications means such as an RFID tag, a Bluetooth or 6L0WPAN ("IPv6 over Low Power Wireless Personal Area Networks”) transmitter, or the like.
• the objects 12, 13, 14 included in the expected set 15 are capable of communicating wirelessly with the tracker device 16, in the form of a mobile phone, a smartphone, a mobile terminal, a UE, a tablet, a smartwatch, or any other appropriate wireless communications device, being equipped with a processing unit and a wireless communications interface.
• the tracker device 16 may communicate with objects capable of wireless communications via any appropriate wireless technology, such as RFID, Bluetooth, 6L0WPAN, any cellular
• the tracker device 16 communicates with one or more remotely located network nodes, such as for instance an application server 17 or one or more nodes of a cloud environment which is/are accessible by the tracker device 16, for fetching stored data, for storing data, or for having the network node perform any computing functions on behalf of the tracker device 16.
• network nodes such as for instance an application server 17 or one or more nodes of a cloud environment which is/are accessible by the tracker device 16, for fetching stored data, for storing data, or for having the network node perform any computing functions on behalf of the tracker device 16.
• the expected set 15 of objects is associated with a particular activity in which the user 10 of the tracker device 16 is to partake, in this exemplifying embodiment an activity defined as "going to work".
• an activity defined as "going to work” is associated with the tracker device 16 and/or the server 17:
• Expected_Set_of_Devices "Wallet, Key, Work Pass”
• the activity can be specified in many different ways, e.g., as a time window set to "Any Weekday, 07:00-08:00".
• the activity may further specify a location criterion which is associated with the tracker device 16 used by the user 10.
• the location criterion comprised in the activity can be specified in numerous ways depending on the particular implementation, in this exemplifying embodiment for instance as "Leave Home”.
• the tracker device 16 will accordingly detect indirectly whether at least one of the objects 12, 13, 14 in the expected set 15 complies with this predetermined location criterion by determining whether it complies with this predetermined location criterion itself.
• a specified activity is performed by the user 10.
• the user 10 is considered to perform the activity upon leaving the home premises 11, which is detected by means of the tracker device 16 leaving the home premises 11 during the time window specified for the activity ("Any Weekday, 07:00-08:00").
• a change in location is detected, by detection a change in location of the tracker device 16 from a first location ("on home premises") to a second location (“off home premises”).
• step S 102 information is acquired identifying an expected set 15 of objects which are associated with the detected activity, in this case the wallet 12, the home key 13, and the work pass 14. It can be envisaged that each object is given a unique numerical identifier.
• step S103 If it is determined in step S103 that any one or more of the objects included in the expected set 15, e.g., the wallet 12, is not in proximity to the tracker device 16 when the tracker device leaves the home premises 11 of the user 10 during the time window specified for the activity, the user 10 is notified thereof in step S 104.
• the respective locations of the objects 12, 13, 14 and the tracker device 16 may be tracked using, e.g., Global Positioning System (GPS).
• GPS Global Positioning System
• the location or position of tracker device 16 is determined using GPS, while the proximity of the objects 12, 13, 14 to the tracker device is detected using, e.g., NFC or any other short-range radio technology between the tracker device 16 and the objects 12, 13, 14.
• the user 10 is advantageously notified accordingly.
• the user 10 is thus made aware that she forgot one or more of the objects of the expected set 15 associated with this particular activity and can go back into her house 11 to pick up any forgotten object of the expected set 15 before leaving for work.
• the user 10 is not notified, even though it could be envisaged that the user 10 is notified that all objects of the expected set 15 have been successfully detected.
• the user 10 is notified by tracker device 16 emitting an audible sound, displaying a message, generating a haptic notification such as a vibration, etc.
• the tracker device 16 may signal another wireless communications device that the user 10 should be notified, for instance by requesting the user's smartwatch to vibrate, or requesting the user's car to not start the engine and/or display a message on the dashboard.
• step S 101 that it is located outside of the home premises 11 (i.e., by detecting a change in its location from a first location to a second location as previously described) on a weekday at 07:00-08:00.
• the tracker device 16 requests from a local data storage in step S 102 information identifying the expected set 15 of objects which are associated with the detected activity, and determines whether it is capable of communicating, e.g., by NFC, with all the objects 12, 13, 14 in the expected set 15 in step S 103.
• the tracker device 16 may measure the strength of a signal submitted by the respective object, and if the signal strength is sufficient, i.e., exceeds a threshold value, the object is considered to be in proximity of the tracker device 16.
• the tracker device 16 notifies the user, and the user 10 is thus advantageously made aware that she forgot one or more of the objects of the expected set 15 associated with this particular activity and can go back into her house 11 to pick up any forgotten object of the expected set 15 before leaving for work.
• Figure 3 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to an embodiment of the invention.
• the tracker device 16 has access to one or more specified activities of the user 10, for instance fetched from a calendar app executing on the user's smartphone
• An alternative approach is to have the tracker device 16 learn activities of the user, and even to associate a learned expected set of objects with each learned activity.
• the tracker device 16 After the tracker device 16 has (1) left the home premises on (2) a weekday at (3) 07:00-08:00 at a number of occasions, it will define the activity "Go To Work" based on these three criteria. Further, by repeatedly detecting a set of objects in its proximity at these occasions, the tracker device 16 will form the expected set of objects and associate the expected set with this activity.
• a database may be maintained at the tracker device 16 specifying a number of activities and an expected set of objects associated with each of the activities:
• Table la Database comprising activities and associated objects.
• At least one object is associated with each activity, thereby creating the expected set of objects.
• One and the same object may be associated with different activities.
• Objectl is comprised in the expected set both for Activity 1 and Activity2.
• the tracker device 16 detects in step S lOl its location, e.g., using GPS, or by detecting that it leaves a coverage area of the user's WLAN. If the location of the tracker device 16 changes from a first location ("on home premises") to a second location ("off home premises") on any weekday at 07:00-08:00, the user is considered to partake in this particular activity ("Go To Work”). It is assumed that this corresponds to Activity 1 in Table la.
• step S102 the tracker device 16 acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device 16 maps the detected activity
• the expected set 15 comprises Objectl, Object2, and Object3, in this example corresponding to the wallet 12, the home key 13, and the work pass 14, respectively.
• the tracker device 16 determines in step S103 whether at least one of the objects 12, 13, 14 in the expected set is not in its proximity, upon the user performing the activity of going to work ("Activityl"). It is in this example assumed that the tracker device 16 communicates with the objects utilizing NFC.
• the tracker device 16 determines whether the objects 12, 13, 14 are in its proximity, for instance by making an attempt to communicate with the objects, or by measuring the strength of a respective signal received from the objects. If the communication attempt is successful, or if the signal strength exceeds a threshold value, the object is considered to be in proximity of the tracker device 16.
• indicator indicating "proximity" for each object can be stored in the database, e.g., in the form of a signal strength threshold defining "proximity" for that specific object.
• the home key 13 and the work pass 14 are in proximity to the tracker device 16, while the wallet 12 is not.
• the tracker device 16 determines in step S103 that the home key 13 ("Object2") and the work pass 14 ("Object3") are in proximity to the tracker device 16, but that the wallet 12 ("Objectl”) is not, thereby concluding from Table la that not all the objects in the expected set for Activityl are in proximity to the tracker device 16.
• the tracker device 16 notifies the user 10 in step S 104 by emitting an audio alert to the user 10, informing her about the lacking wallet 12.
• the tracker device 16 may optionally display a message notifying the user that an expected object is not in the user's 10 proximity, preferably also identifying the missing object by name (e.g., "You forgot your wallet.”).
• Figure 4 illustrates a sequence diagram where the method of monitoring is performed partly or fully at one or more remotely located network nodes, thereby facilitating a cloud solution.
• the network node(s) is/are embodied by the server 17.
• the server 17 has access to one or more specified activities of the user 10, for instance fetched from a calendar app executing on the user's smartphone (exemplified as being the tracker device 16) or from a cloud storage.
• sensor readings such as position or location data may be transmitted from the tracker device 16 to the server 17.
• a database may be maintained at the server 17 specifying a number of activities and an expected set of objects associated with each of the activities, as previously described with reference to Table la.
• the server 17 detects in step S 101 the location of the tracker device 16 using GPS. If the tracker device 16 is leaving the user's 10 home premises 11 on any weekday at 07:00-08:00, the activity ("Go To Work") is detected. Again, it is assumed that this corresponds to Activity 1 in Table la.
• step S102 the server 17 acquires information identifying an expected set of objects which are associated with the detected activity, from the stored database.
• the server 17 maps the detected activity ("Activity 1") to the entries in Table la and concludes that the expected set 15 comprises Objectl, Object2 and Object3, in this example corresponding to the wallet 12, the home key 13, and the work pass 14, respectively.
• the server 17 communicates directly with the objects capable of wireless communication, i.e., the wallet 12, the home key 13 and the work pass 14, for determining their proximity to the tracker device 16 based on, e.g., GPS readings
• the tracker device 16 communicates with the respective object utilizing, e.g., NFC, and provides resulting information to the server 17.
• the server 17 would communicate directly with the objects 12, 13, 14, the method may be undertaken in its entirety "in the cloud", either by the server 17 solely or in cooperation with other remote nodes.
• the server 17 acquires in step S103a information as to which objects actually are in proximity to the tracker device 16 upon the user performing the activity of going to work ("Activity 1").
• the tracker device 16 concludes that the home key 13 and the work pass 14 are in proximity to the tracker device 16, but that the wallet 12 is not, which the tracker device 16 reports accordingly to the server 17.
• the server 17 determines in step S 103 that the home key 13 ("Object2") and the work pass 14 ("Object3") are in proximity to the tracker device 16, but that the wallet 12 ("Objectl”) is not, thereby concluding from Table la that not all the objects in the expected set for Activityl are in proximity to the tracker device 16. As a consequence, the server 17 sends a notification to the user 10 via the tracker device 16 in step S 104, whereby the tracker device 16 emits an audio alert to the user 10 advantageously informing her about her lacking wallet 12.
• the server 17 would communicate directly with the objects 12, 13, 14, and notify the user 10 via, e.g., her smartwatch (not shown), the tracker device 16 need not take any active part in the monitoring, not even causing an audio alert.
• Figure 5 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to another embodiment.
• this embodiment may also be implemented by a remotely located network node, such as the server 17.
• all objects which are in proximity to the tracker device 16 are determined upon detecting that the user 10 partakes in a specified activity.
• only the objects comprised in the expected set are detected as being in proximity to the tracker device 16. Accordingly, as soon as all objects 12, 13, 14 of the expected set have been detected, there is no need to continue and detect any further proximate objects.
• the objects determined to be in proximity to the tracker device 16 are referred to as an actual set of objects.
• the tracker device 16 detects in step S101 its location, e.g., using GPS. If the tracker device 16 is leaving the user's 10 home premises 11 on any weekday at 07:00-08:00, the user is considered to partake in the activity ("Go To Work"). It is assumed that this corresponds to Activity 1 in Table la.
• step S102 the tracker device 16 acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device 16 maps the detected activity ("Activityl") to the entries in Table la and concludes that the expected set 15 comprises Objectl, Object2 and Object3, in this example corresponding to the wallet
• the tracker device 16 determines in step S103b the actual set of objects being in proximity of the tracker device 16. As is illustrated in Figure 5, the tracker device 16 determines that the home key 13 and the work pass 14 are in proximity to the tracker device 16, but that the wallet 12 is not.
• the tracker device 16 further determines that a smartwatch 18 ("Object4") is in proximity of the tracker device 16, for instance by signalling based on Bluetooth or even via a Wireless Local Area Network (WLAN), commonly referred to as "WiFi”.
• a smartwatch 18 (“Object4") is in proximity of the tracker device 16, for instance by signalling based on Bluetooth or even via a Wireless Local Area Network (WLAN), commonly referred to as "WiFi”.
• WLAN Wireless Local Area Network
• step S 103 the tracker device 16 determines whether any object
• the tracker device 16 notifies the user 10 in step S 104 by emitting an audio alert and/or displaying a notification to the user 10, advantageously informing her about the lacking wallet 12.
• Figure 6 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to still another embodiment.
• this embodiment may also be implemented at a remotely located network node, such as the server 17.
• step S104 As in the embodiment of Figure 5, all objects being in proximity to the tracker device 16 upon detection of the user 10 performing a specified activity are determined, thereby forming an actual set. However, in addition to the steps of the embodiment described with reference to Figure 5, after (or before) having notified the user 10 in step S104 that the wallet 12 included in the expected set has not been detected as being in proximity to the tracker device 16, the user is queried in step S 105 as to whether any objects of the determined actual set are to be added to the expected set which is associated with the detected activity.
• step S 106 The user responds in step S 106, in this particular example with the response that the smartwatch 18 is to be added to the expected set for Activity 1.
• the tracker device 16 will thus update its database of Table la in step S 107, resulting in updated Table lb:
• Table lb Updated database comprising activities and associated objects.
• Figure 7 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to still a further embodiment.
• this embodiment may also be implemented at a remotely located network node, such as the server 17.
• step S 104 after having notified the user 10 in step S 104 that the wallet 12 included in the expected set has not been detected as being in proximity to the tracker device 16, the
• step S108 to indicate as to whether one or more objects of the expected set associated with the detected activity are to be removed from the expected set to create an updated expected set for the detected activity.
• the user 10 indicates that the wallet 12 ("Objectl") is to be removed from the expected set illustrated in Table la, wherein the tracker device 16 updates its database of Table la in step S 109, resulting in updated Table lc:
• Table lc Updated database comprising activities and associated objects.
• Figure 8 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to yet another embodiment.
• this embodiment may also be implemented at a remotely located network node, such as the server 17.
• a remotely located network node such as the server 17.
• all objects being in proximity to the tracker device 16 upon detection of the user 10 performing a specified activity is determined, thereby forming an actual set.
• This embodiment is advantageous since it facilitates machine learning, as will be described in detail in the following.
• Table 2a Database comprising activities and associated objects.
• the tracker device 16 again has access to one or more specified activities of the user 10, for instance fetched from a calendar app executing on the user's smartphone (exemplified here as being the tracker device 16), or learned by means of machine learning as previously discussed.
• the tracker device 16 detects in step S 101 its location using, e.g., GPS. If the tracker device 16 is leaving the user's 10 home premises 11 on any weekday at 07:00-08:00, the user is considered to partake in new Activity 1, which is learned by the tracker device 16 and added to Table 2a. Thereafter, in step S102, the tracker device 16 acquires information identifying an expected set of objects which are associated with the detected activity from the stored database. To this end, the tracker device 16 maps the detected activity ("Activity 1") to the entries in Table 2a and concludes that expected set associated with Activity 1 not yet comprises any objects.
• Activity 1 the detected activity
• the tracker device 16 determines in step S103b the actual set of objects being in proximity of the tracker device 16. As is illustrated in Figure 8, the tracker device 16 concludes that the wallet 12, the home key 13, and the work pass 14, are in proximity to the tracker device 16.
• step S 103c the tracker device 16 advantageously associates the actual set of objects 12, 13, 14 with the detected activity as a new expected set of objects, and thus updates Table 2a, resulting in Table 2b:
• Table 2b Updated database comprising activities and associated objects.
• machine learning can be applied to record activities and objects in the database as illustrated in Tables 2and b, and to create appropriate associations between expected sets and corresponding activities.
• machine learning such as association rule mining and/or frequent itemsets (discussed, e.g., in Chapter 6 of "Mining of Massive Datasets" by
• J. Leskovec A. Rajaraman, and J. D. Ullman
• J. Leskovec A. Rajaraman, and J. D. Ullman
• a trackder device 16 such as a mobile phone or smartphone of a user, possibly in combination with further sensing devices, is used for building a database of activities and corresponding expected sets of devices to be associated with the activities.
• the tracker device 16 registers that when the user leaves at home during a weekday at 07:00-08:00, she usually brings her wallet 12, home key 13, and work pass 14. Upon having registered that
• the tracker device 16 may for instance stipulate that any object to be included in the expected set must fulfill a certain probability threshold, such as having been carried by the user at 80% of the occasions when the user performed the activity.
• Figure 9 illustrates a sequence diagram where the method of monitoring is performed in its entirety by the tracker device 16 according to still another embodiment.
• this embodiment may also be implemented at a remotely located network node, such as the server 17.
• the tracker device 16 queries the user 10 in step S 103d whether the objects 12, 13, 14 of the determined actual of objects are to be stored as a new expected set for the detected activity.
• the user 10 responds to the query in step S103e, for instance by indicating on a screen of the tracker device 16 (being, e.g., a smartphone) whether all determined objects of the actual set are to be associated with the detected activity as the new expected set, or whether a subset of the objects of the actual set is to be associated with the detected activity as the new expected set, in response to which the tracker device 16 advantageously associates the objects 12, 13, 14 indicated by the user 10 with the detected activity as the new expected set of objects, and thus updates Table 2a, resulting in Table 2b.
• the tracker device 16 advantageously associates the objects 12, 13, 14 indicated by the user 10 with the detected activity as the new expected set of objects, and thus updates Table 2a, resulting in Table 2b.
• a doctor is called upon to deal with an activity in the form of an emergency situation where a patient experiences high blood sugar (hyperglycaemia).
• the expected set associated with this activity may thus comprise (a) a dose of insulin and (b) an injection device (e.g., being RFID-tagged). If the doctor has forgotten to pack the insulin and injection upon leaving his clinic, his mobile phone detects the absence and raises an alarm, so that the doctor realizes this before he leaves his clinic.
• the case file may be RFID-tagged to ensure that his smartwatch will sound an alarm if he leaves his office for the court proceedings without the case file.
• the activity may thus specify a date and time of the picnic, and further weather conditions acquired for instance from a weather forecast. Hence, if she leaves home at the specified date and time, and the forecast predicts bad weather, her smartphone will notify her if she does not bring the handy-cam and/or the umbrella.
• the communications device may be detected based on at least one, a combination, or a pattern, of: a location of the wireless communications device or a change thereof, a motion pattern of the wireless communications device or a change thereof, a date, a time of day, a calendar event, a communication event, or even current weather conditions.
• a location of the wireless communications device or a change thereof a motion pattern of the wireless communications device or a change thereof
• a date a time of day
• a calendar event a communication event, or even current weather conditions.
• time windows such as a particular time of the day, or a particular weekday derived for instance from a meeting event or itinerary
• the user's smartwatch alerts the user in case skin temperature measured by an IoT-type temperatures arranged in a garment of the user exceeds a threshold value, the activity being defined e.g. as "User Catching Fever”.
• the steps of the method performed by the tracker device 16, or the server 17, or a distributed cloud solution are in practice performed by a processing unit 20 embodied in the form of one or more microprocessors arranged to execute a computer program 21 downloaded to a suitable storage medium 22 associated with the microprocessor, such as a Random Access Memory (RAM), a Flash memory or a hard disk drive.
• the processing unit 20 is arranged to cause the device 16 to carry out the method according to embodiments when the appropriate computer program 31 comprising computer- executable instructions is downloaded to the storage medium 32 and executed by the processing unit 30.
• the storage medium 32 may also be a computer program product comprising the computer program 31.
• the computer program 31 may be transferred to the storage medium 32 by means of a suitable computer program product, such as a Digital Versatile Disc (DVD) or a memory stick.
• a suitable computer program product such as a Digital Versatile Disc (DVD) or a memory stick.
• the computer program 31 may be downloaded to the storage medium 32 over a network.
• the processing unit 30 may alternatively be embodied in the form of a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc.
• Figure 11 illustrates a device 16 configured to monitor objects capable of wireless communication.
• the device 16 comprises detecting means 30 adapted to detect an activity performed by a user of a wireless communications device, acquiring means 31 adapted to acquire information identifying an expected set of objects which are associated with the detected activity, and determining means 32 adapted to determine whether at least one of the objects in the expected set is not in proximity of the wireless communications device. Further, the device 16 comprises notifying means 33 adapted to notify the user that at least one of the objects in the expected set is not in proximity of the wireless communications device
• the device 16 may further comprise a communications interface for receiving and providing information, and further a local storage for storing data, and may (in analogy with that previously discussed) be implemented by a processor embodied in the form of one or more microprocessors arranged to execute a computer program downloaded to a suitable storage medium associated with the microprocessor, such as a RAM, a Flash memory or a hard disk drive.
• a processor embodied in the form of one or more microprocessors arranged to execute a computer program downloaded to a suitable storage medium associated with the microprocessor, such as a RAM, a Flash memory or a hard disk drive.

Landscapes

• Engineering & Computer Science (AREA)
• Computer Networks & Wireless Communication (AREA)
• Signal Processing (AREA)
• Theoretical Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Computer Security & Cryptography (AREA)
• Computer Hardware Design (AREA)
• Software Systems (AREA)
• Emergency Management (AREA)
• General Engineering & Computer Science (AREA)
• Business, Economics & Management (AREA)
• Databases & Information Systems (AREA)
• Environmental & Geological Engineering (AREA)
• Human Computer Interaction (AREA)
• Emergency Alarm Devices (AREA)
• Telephone Function (AREA)
• Telephonic Communication Services (AREA)
• Alarm Systems (AREA)

Priority Applications (1)

Applications Claiming Priority (1)

Related Child Applications (2)

Publications (3)

Family

ID=60783955

Family Applications (2)

Family Applications Before (1)

Country Status (5)

Families Citing this family (19)

Family Cites Families (23)

• 2016
  • 2016-06-20 WO PCT/IN2016/050190 patent/WO2017221260A1/en unknown
  • 2016-06-20 CN CN201680086863.2A patent/CN109417680B/zh active Active
  • 2016-06-20 EP EP22206968.4A patent/EP4156724B1/de active Active
  • 2016-06-20 EP EP16906200.7A patent/EP3473023B1/de active Active
  • 2016-06-20 US US16/310,872 patent/US11595784B2/en active Active
  • 2016-06-20 CN CN202110831142.2A patent/CN113543029B/zh active Active
  • 2016-06-20 DK DK16906200.7T patent/DK3473023T3/da active
• 2023
  • 2023-01-18 US US18/155,795 patent/US11902859B2/en active Active

Also Published As

Similar Documents

Legal Events